When terrorist attacks occur, it leads the public in search of a terrorist profile. Although studies have shown that no one “terrorist type” exits, this analysis will provide some common demographic characteristics of individuals that were charged with or died in terrorist attacks. It will also analyze the impact of online radicalization in the perpetrators attempting to conduct terrorist attacks.The data have been taken from a dataset called “Terrorism Cases Since 2001” by Carl Lewis from The New America Foundation and covers information about perpetrators of terrorism cases from 2001 to 2016. Lewis states that a perpetrator’s citizen status should be noted in light of President Trump’s 2017 Executive Order, which aimed to ban individuals from Muslim majority countries from entering the United States.
Young, unmarried men are more likely to be radicalized online and subsequently carry out terrorist attacks.
In addition to testing the above hypothesis, this analysis has the following objectives:
This analysis examines several key variables to better understand common demographic characteristics. Marital status allows us to understand the relationship status of perpetrators and provides context to understand their social ties. Lastly, online radicalization serves as a binary variable to understand the role of social media platforms in the radicalization process, and will serve as the outcome variable for the logistic regression model.
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## (`stat_count()`).
The ages of perpetrators range from a minimum of 15 to a maximum of 76 years old. The median age, which represents the midpoint of the age distribution, is 26, indicating that half of the perpetrators are younger than 26 and half are older. The average age of terrorist attack perpetrators in the data set is 29 years old with slight skew towards older ages due to the presence of outliers. The quartile values further describe the age distribution, with 25% of perpetrators aged 22 or younger and 25% aged 33 or older.
The largest proportion of perpetrators, accounting for 170 individuals, is classified as unmarried or single, representing a significant portion of the dataset. Following this, the next most common status is married, with 145 individuals identified as such. A smaller number of individuals are reported as divorced, split, or widowed, with 20, 5, and 2 individuals respectively. 55 individuals in the dataset had an unknown marital status.
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| term | estimate | std.error | statistic | p.value |
|---|---|---|---|---|
| (Intercept) | -26.56607 | 109808.439 | -0.0002419 | 0.999807 |
| age | 0.00000 | 2144.928 | 0.0000000 | 1.000000 |
| marital_statusMarried | 0.00000 | 85161.976 | 0.0000000 | 1.000000 |
| marital_statusSplit | 0.00000 | 178073.659 | 0.0000000 | 1.000000 |
| marital_statusUnknown | 0.00000 | 95528.743 | 0.0000000 | 1.000000 |
| marital_statusUnmarried | 0.00000 | 87541.800 | 0.0000000 | 1.000000 |
| marital_statusWidowed | 0.00000 | 264505.173 | 0.0000000 | 1.000000 |
Based on the logistical regression model, age and marital status have a p-value of 1. This p-value shows that there is no significant relationship between age, marital status, and online radicalization. Specifically, age does not appear to be a significant predictor of online radicalization in this study. The same is said for marital status, where a perpetrator’s marital status does not have a statistically significant impact on online radicalization among young adults in the analyzed dataset.
The was downloaded from the “Terrorism Cases, 2001 - 2016” which was downloaded from Data World: https://data.world/carlvlewis/terrorism-cases-2001-2016. More information on the project can also be found here: https://www.newamerica.org/future-security/reports/terrorism-in-america/.